Prebiopsy bpMRI and hematological parameter-based risk scoring model for predicting outcomes in biopsy-naive men with PSA 4–20 ng/mL
Abstract Excessive prostate biopsy is a common problem for clinicians. Although some hematological and bi-parametric magnetic resonance imaging (bpMRI) parameters might help increase the rate of positive prostate biopsies, there is a lack of studies on whether their combination can further improve c...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2022-12-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-022-26242-7 |
| _version_ | 1797977409221296128 |
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| author | Yuxin Zheng Wang Li Yang Zhang Chi Zhang Junqi Wang Peng Ge |
| author_facet | Yuxin Zheng Wang Li Yang Zhang Chi Zhang Junqi Wang Peng Ge |
| author_sort | Yuxin Zheng |
| collection | DOAJ |
| description | Abstract Excessive prostate biopsy is a common problem for clinicians. Although some hematological and bi-parametric magnetic resonance imaging (bpMRI) parameters might help increase the rate of positive prostate biopsies, there is a lack of studies on whether their combination can further improve clinical detection efficiency. We retrospectively enrolled 394 patients with PSA levels of 4–20 ng/mL who underwent prebiopsy bpMRI during 2010–2021. Based on bpMRI and hematological indicators, six models and a nomogram were constructed to predict the outcomes of biopsy. Furthermore, we constructed and evaluated a risk scoring model based on the nomogram. Age, prostate-specific antigen (PSA) density (PSAD), systemic immune-inflammation index, cystatin C level, and the Prostate Imaging Reporting and Data System (PI-RADS) v2.1 score were significant predictors of prostate cancer (PCa) on multivariable logistic regression analyses (P < 0.05) and the five parameters were used to construct the XYFY nomogram. The area under the receiver operating characteristic (ROC) curve (AUC) of the nomogram was 0.916. Based on the nomogram, a risk scoring model (XYFY risk model) was constructed and then we divided the patients into low-(XYFY score: < 95), medium-(XYFY score: 95–150), and, high-risk (XYFY score: > 150) groups. The predictive values for diagnosis of PCa and clinically-significant PCa among the three risk groups were 3.0%(6/201), 41.8%(51/122), 91.5%(65/71); 0.5%(1/201), 19.7%(24/122), 60.6%(43/71), respectively. In conclusion, in this study, we used hematological and bpMRI parameters to establish and internally validate a XYFY risk scoring model for predicting the biopsy outcomes for patients with PSA levels of 4–20 ng/mL and this risk model would support clinical decision-making and reduce excessive biopsies. |
| first_indexed | 2024-04-11T05:06:27Z |
| format | Article |
| id | doaj.art-703f1293daf34d0bb456c81b9f421cb5 |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-04-11T05:06:27Z |
| publishDate | 2022-12-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-703f1293daf34d0bb456c81b9f421cb52022-12-25T12:17:26ZengNature PortfolioScientific Reports2045-23222022-12-0112111010.1038/s41598-022-26242-7Prebiopsy bpMRI and hematological parameter-based risk scoring model for predicting outcomes in biopsy-naive men with PSA 4–20 ng/mLYuxin Zheng0Wang Li1Yang Zhang2Chi Zhang3Junqi Wang4Peng Ge5Department of Urology, The Affiliated Hospital of Xuzhou Medical UniversityDepartment of Urology, The Affiliated Hospital of Xuzhou Medical UniversityDepartment of Urology, The Affiliated Hospital of Xuzhou Medical UniversityDepartment of Urology, The Affiliated Hospital of Xuzhou Medical UniversityDepartment of Urology, The Affiliated Hospital of Xuzhou Medical UniversityDepartment of Urology, The Affiliated Hospital of Xuzhou Medical UniversityAbstract Excessive prostate biopsy is a common problem for clinicians. Although some hematological and bi-parametric magnetic resonance imaging (bpMRI) parameters might help increase the rate of positive prostate biopsies, there is a lack of studies on whether their combination can further improve clinical detection efficiency. We retrospectively enrolled 394 patients with PSA levels of 4–20 ng/mL who underwent prebiopsy bpMRI during 2010–2021. Based on bpMRI and hematological indicators, six models and a nomogram were constructed to predict the outcomes of biopsy. Furthermore, we constructed and evaluated a risk scoring model based on the nomogram. Age, prostate-specific antigen (PSA) density (PSAD), systemic immune-inflammation index, cystatin C level, and the Prostate Imaging Reporting and Data System (PI-RADS) v2.1 score were significant predictors of prostate cancer (PCa) on multivariable logistic regression analyses (P < 0.05) and the five parameters were used to construct the XYFY nomogram. The area under the receiver operating characteristic (ROC) curve (AUC) of the nomogram was 0.916. Based on the nomogram, a risk scoring model (XYFY risk model) was constructed and then we divided the patients into low-(XYFY score: < 95), medium-(XYFY score: 95–150), and, high-risk (XYFY score: > 150) groups. The predictive values for diagnosis of PCa and clinically-significant PCa among the three risk groups were 3.0%(6/201), 41.8%(51/122), 91.5%(65/71); 0.5%(1/201), 19.7%(24/122), 60.6%(43/71), respectively. In conclusion, in this study, we used hematological and bpMRI parameters to establish and internally validate a XYFY risk scoring model for predicting the biopsy outcomes for patients with PSA levels of 4–20 ng/mL and this risk model would support clinical decision-making and reduce excessive biopsies.https://doi.org/10.1038/s41598-022-26242-7 |
| spellingShingle | Yuxin Zheng Wang Li Yang Zhang Chi Zhang Junqi Wang Peng Ge Prebiopsy bpMRI and hematological parameter-based risk scoring model for predicting outcomes in biopsy-naive men with PSA 4–20 ng/mL Scientific Reports |
| title | Prebiopsy bpMRI and hematological parameter-based risk scoring model for predicting outcomes in biopsy-naive men with PSA 4–20 ng/mL |
| title_full | Prebiopsy bpMRI and hematological parameter-based risk scoring model for predicting outcomes in biopsy-naive men with PSA 4–20 ng/mL |
| title_fullStr | Prebiopsy bpMRI and hematological parameter-based risk scoring model for predicting outcomes in biopsy-naive men with PSA 4–20 ng/mL |
| title_full_unstemmed | Prebiopsy bpMRI and hematological parameter-based risk scoring model for predicting outcomes in biopsy-naive men with PSA 4–20 ng/mL |
| title_short | Prebiopsy bpMRI and hematological parameter-based risk scoring model for predicting outcomes in biopsy-naive men with PSA 4–20 ng/mL |
| title_sort | prebiopsy bpmri and hematological parameter based risk scoring model for predicting outcomes in biopsy naive men with psa 4 20 ng ml |
| url | https://doi.org/10.1038/s41598-022-26242-7 |
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